
CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
--mode shots \
--save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--shots 40 \
--threshold 0 \
--which_repre_layers 4,8,16,32,64,128,256 \
--multi_class \
--supervised_pkl save_seg/supervised/exp16-222shot-reso256-augTrue/checkpoint/0_best.pth \
--seed 0

# CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
# --mode shots \
# --save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 30 \
# --threshold 0 \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --multi_class \
# --supervised_pkl save_seg/supervised/exp16-222shot-reso256-augTrue/checkpoint/0_best.pth \
# --seed 0
# CUDA_VISIBLE_DEVICES=5 python auto-shot-2d.py \
# --mode SegNet \
# --save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 15 \
# --threshold 0 \
# --epochs 1000 \
# --batch_size 5 \
# --which_net BiFPN \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --seed 0 \
# --split 72 8 20 \
# --w_steps 1000 \
# --length 128 \
# --combine

# CUDA_VISIBLE_DEVICES=5 python auto-shot-2d.py \
# --n_train 3 \
# --mode U-Net \
# --save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --out_dir save_seg/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --data_dir data/US \
# --shots 15 \
# --threshold 0 \
# --epochs 2000 \
# --batch_size 5 \
# --split 72 8 20 \
# --which_net BiFPN \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --w_steps 1000 \
# --length 128 \
# --combine \
# --aug \
# --seed 0

CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
--mode SegNet \
--save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--shots 35 \
--threshold 0 \
--epochs 1000 \
--batch_size 5 \
--which_net BiFPN \
--which_repre_layers 4,8,16,32,64,128,256 \
--seed 0 \
--split 72 8 20 \
--w_steps 1000 \
--length 128 \
--combine

CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
--n_train 3 \
--mode U-Net \
--save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--out_dir save_seg/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--data_dir data/US \
--shots 35 \
--threshold 0 \
--epochs 2000 \
--batch_size 5 \
--split 72 8 20 \
--which_net BiFPN \
--which_repre_layers 4,8,16,32,64,128,256 \
--w_steps 1000 \
--length 128 \
--combine \
--aug \
--seed 0

CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
--mode SegNet \
--save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--shots 40 \
--threshold 0 \
--epochs 1000 \
--batch_size 5 \
--which_net BiFPN \
--which_repre_layers 4,8,16,32,64,128,256 \
--seed 0 \
--split 72 8 20 \
--w_steps 1000 \
--length 128 \
--combine

CUDA_VISIBLE_DEVICES=4 python auto-shot-2d.py \
--n_train 3 \
--mode U-Net \
--save_dir save/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--out_dir save_seg/00018-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
--data_dir data/US \
--shots 40 \
--threshold 0 \
--epochs 2000 \
--batch_size 5 \
--split 72 8 20 \
--which_net BiFPN \
--which_repre_layers 4,8,16,32,64,128,256 \
--w_steps 1000 \
--length 128 \
--combine \
--aug \
--seed 0
# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --mode shots \
# --save_dir save/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 128 \
# --threshold 0 \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --multi_class \
# --supervised_pkl save_seg/supervised/exp0-72shot-reso160-augTrue/checkpoint/2_best.pth \
# --seed 0


# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --mode SegNet \
# --save_dir save/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 128 \
# --threshold 0 \
# --epochs 1000 \
# --batch_size 5 \
# --which_net L \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --seed 0 \
# --split 72 8 20 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine

# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --mode SegNet \
# --save_dir save/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 128 \
# --threshold 0 \
# --epochs 1000 \
# --batch_size 5 \
# --which_net BiFPN \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --seed 0 \
# --split 72 8 20 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine

# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --mode SegNet \
# --save_dir save/00011-GAN_OASIS-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --shots 128 \
# --threshold 0 \
# --epochs 1000 \
# --batch_size 5 \
# --which_net L \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --seed 0 \
# --split 72 8 20 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine
# # =====================================================================--batch_size 16 \


# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --n_train 3 \
# --mode U-Net \
# --save_dir save/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --out_dir save_seg/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --data_dir data/CANDI-128-160 \
# --shots 128 \
# --threshold 0 \
# --epochs 5000 \
# --batch_size 5 \
# --split 72 8 20 \
# --which_net L \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine \
# --resize \
# --aug \
# --seed 0

# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --n_train 3 \
# --mode U-Net \
# --save_dir save/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --out_dir save_seg/00010-images-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --data_dir data/CANDI-128-160 \
# --shots 128 \
# --threshold 0 \
# --epochs 5000 \
# --batch_size 5 \
# --split 72 8 20 \
# --which_net BiFPN \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine \
# --resize \
# --aug \
# --seed 0

# CUDA_VISIBLE_DEVICES=6 python auto-shot.py \
# --n_train 3 \
# --mode U-Net \
# --save_dir save/00011-GAN_OASIS-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --out_dir ./save_seg/00011-GAN_OASIS-mirror-low_shot-kimg25000-batch32-color-translation-cutout \
# --data_dir data/OASIS-128-160 \
# --shots 128 \
# --threshold 0 \
# --epochs 5000 \
# --batch_size 5 \
# --split 72 8 20 \
# --which_net L \
# --which_repre_layers 4,8,16,32,64,128,256 \
# --w_steps 1000 \
# --length 128 \
# --multi_class \
# --combine \
# --resize \
# --seed 0